scholarly journals Assessing the clinical utility of genetic risk scores for targeted cancer screening

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Carly A. Conran ◽  
Zhuqing Shi ◽  
William Kyle Resurreccion ◽  
Rong Na ◽  
Brian T. Helfand ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Primary Care ◽  
High Risk ◽  
Risk Score ◽  
Genetic Risk ◽  
Clinical Utility ◽  
Low Risk ◽  
Risk Scores ◽  
Average Risk ◽  
Genetic Risk Scores

Abstract Background Genome-wide association studies have identified thousands of disease-associated single nucleotide polymorphisms (SNPs). A subset of these SNPs may be additively combined to generate genetic risk scores (GRSs) that confer risk for a specific disease. Although the clinical validity of GRSs to predict risk of specific diseases has been well established, there is still a great need to determine their clinical utility by applying GRSs in primary care for cancer risk assessment and targeted intervention. Methods This clinical study involved 281 primary care patients without a personal history of breast, prostate or colorectal cancer who were 40–70 years old. DNA was obtained from a pre-existing biobank at NorthShore University HealthSystem. GRSs for colorectal cancer and breast or prostate cancer were calculated and shared with participants through their primary care provider. Additional data was gathered using questionnaires as well as electronic medical record information. A t-test or Chi-square test was applied for comparison of demographic and key clinical variables among different groups. Results The median age of the 281 participants was 58 years and the majority were female (66.6%). One hundred one (36.9%) participants received 2 low risk scores, 99 (35.2%) received 1 low risk and 1 average risk score, 37 (13.2%) received 1 low risk and 1 high risk score, 23 (8.2%) received 2 average risk scores, 21 (7.5%) received 1 average risk and 1 high risk score, and no one received 2 high risk scores. Before receiving GRSs, younger patients and women reported significantly more worry about risk of developing cancer. After receiving GRSs, those who received at least one high GRS reported significantly more worry about developing cancer. There were no significant differences found between gender, age, or GRS with regards to participants’ reported optimism about their future health neither before nor after receiving GRS results. Conclusions Genetic risk scores that quantify an individual’s risk of developing breast, prostate and colorectal cancers as compared with a race-defined population average risk have potential clinical utility as a tool for risk stratification and to guide cancer screening in a primary care setting.

scholarly journals Assessing the Clinical Utility of Genetic Risk Scores for Targeted Cancer Screening

2020 ◽  
Author(s):  
Carly Ann Conran ◽  
Zhuqing Shi ◽  
William Kyle Resurreccion ◽  
Rong Na ◽  
Brian T. Helfand ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Primary Care ◽  
High Risk ◽  
Risk Score ◽  
Genetic Risk ◽  
Clinical Utility ◽  
Low Risk ◽  
Risk Scores ◽  
Average Risk ◽  
Genetic Risk Scores

Abstract Background: Genome-wide association studies have identified thousands of disease-associated single nucleotide polymorphisms (SNPs). A subset of these SNPs may be additively combined to generate genetic risk scores (GRSs) that confer risk for a specific disease. Although the clinical validity of GRSs to predict risk of specific diseases has been well established, there is still a great need to determine their clinical utility by applying GRSs in primary care for cancer risk assessment and targeted intervention.Methods: This clinical study involved 281 primary care patients without a personal history of breast, prostate or colorectal cancer who were 40-70 years old. DNA was obtained from a pre-existing biobank at NorthShore University HealthSystem. GRSs for colorectal cancer and breast or prostate cancer were calculated and shared with participants through their primary care provider. Additional data was gathered using questionnaires as well as electronic medical record information. A t-test or Chi-square test was applied for comparison of demographic and key clinical variables among different groups.Results: The median age of the 281 participants was 58 years and the majority were female (66.6%). One hundred one (36.9%) participants received 2 low risk scores, 99 (35.2%) received 1 low risk and 1 average risk score, 37 (13.2%) received 1 low risk and 1 high risk score, 23 (8.2%) received 2 average risk scores, 21 (7.5%) received 1 average risk and 1 high risk score, and no one received 2 high risk scores. Before receiving GRSs, younger patients and women reported significantly more worry about risk of developing cancer. After receiving GRSs, those who received at least one high GRS reported significantly more worry about developing cancer. There were no significant differences found between gender, age, or GRS with regards to participants’ reported optimism about their future health neither before nor after receiving GRS results.Conclusions: Genetic risk scores that quantify an individual’s risk of developing breast, prostate and colorectal cancers as compared with a race-defined population average risk have potential clinical utility as a tool for risk stratification and to guide cancer screening in a primary care setting.

scholarly journals Identifying individuals with high risk of Alzheimer’s disease using polygenic risk scores

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ganna Leonenko ◽  
Emily Baker ◽  
Joshua Stevenson-Hoare ◽  
Annerieke Sierksma ◽  
Mark Fiers ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Score ◽  
Genetic Risk ◽  
Prediction Accuracy ◽  
Genetic Risk Score ◽  
Low Risk ◽  
Risk Scores ◽  
Sample Mean ◽  
Polygenic Risk ◽  
Reliable Identification

AbstractPolygenic Risk Scores (PRS) for AD offer unique possibilities for reliable identification of individuals at high and low risk of AD. However, there is little agreement in the field as to what approach should be used for genetic risk score calculations, how to model the effect of APOE, what the optimal p-value threshold (pT) for SNP selection is and how to compare scores between studies and methods. We show that the best prediction accuracy is achieved with a model with two predictors (APOE and PRS excluding APOE region) with pT<0.1 for SNP selection. Prediction accuracy in a sample across different PRS approaches is similar, but individuals’ scores and their associated ranking differ. We show that standardising PRS against the population mean, as opposed to the sample mean, makes the individuals’ scores comparable between studies. Our work highlights the best strategies for polygenic profiling when assessing individuals for AD risk.

scholarly journals Alternative Splicing Events in Tumor Immune Infiltration in Colorectal Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Jian-yu Shi ◽  
Yan-yan Bi ◽  
Bian-fang Yu ◽  
Qing-feng Wang ◽  
Dan Teng ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Alternative Splicing ◽  
High Risk ◽  
Risk Score ◽  
Immune Cell ◽  
Risk Model ◽  
Low Risk ◽  
Risk Scores ◽  
Immune Cell Infiltration ◽  
Immune Infiltration

Despite extensive research, the exact mechanisms involved in colorectal cancer (CRC) etiology and pathogenesis remain unclear. This study aimed to examine the correlation between tumor-associated alternative splicing (AS) events and tumor immune infiltration (TII) in CRC. We analyzed transcriptome profiling and clinical CRC data from The Cancer Genome Atlas (TCGA) database and lists of AS-related and immune-related signatures from the SpliceSeq and Innate databases, respectively to develop and validate a risk model of differential AS events and subsequently a TII risk model. We then conducted a two-factor survival analysis to study the association between TII and AS risk and evaluated the associations between immune signatures and six types of immune cells based on the TIMER database. Subsequently, we studied the distribution of six types of TII cells in high- and low-risk groups for seven AS events and in total. We obtained the profiles of AS events/genes for 484 patients, which included 473 CRC tumor samples and 41 corresponding normal samples, and detected 22581 AS events in 8122 genes. Exon Skip (ES) (8446) and Mutually Exclusive Exons (ME) (74) exhibited the most and fewest AS events, respectively. We then classified the 433 patients with CRC into low-risk (n = 217) and high-risk (n = 216) groups based on the median risk score in different AS events. Compared with patients with low-risk scores (mortality = 11.8%), patients with high-risk scores were associated with poor overall survival (mortality = 27.6%). The risk score, cancer stage, and pathological stage (T, M, and N) were closely correlated with prognosis in patients with CRC (P &lt; 0.001). We identified 6479 differentially expressed genes from the transcriptome profiles of CRC and intersected 468 differential immune-related signatures. High-AS-risk and high-TII-risk predicted a poor prognosis in CRC. Different AS types were associated with different TII risk characteristics. Alternate Acceptor site (AA) and Alternate Promoter (AP) events directly affected the concentration of CD4T cells, and the level of CD8T cells was closely correlated with Alternate Terminator (AT) and Exon Skip (ES) events. Thus, the concentration of CD4T and CD8T cells in the CRC immune microenvironment was not specifically modulated by AS. However, B cell, dendritic cell, macrophage, and neutrophilic cell levels were strongly correlated with AS events. These results indicate adverse associations between AS event risk levels and immune cell infiltration density. Taken together, our findings show a clear association between tumor-associated alternative splicing and immune cell infiltration events and patient outcome and could form a basis for the identification of novel markers and therapeutic targets for CRC and other cancers in the future.

scholarly journals An immune-related lncRNA signature as a prognostic immunotherapy target for colon cancer

2020 ◽  
Author(s):  
Bin Wu ◽  
Yi Yao ◽  
Yi Dong ◽  
Si Qi Yang ◽  
Deng Jing Zhou ◽  
...  
Keyword(s):  
Colon Cancer ◽  
High Risk ◽  
Risk Score ◽  
Enrichment Analysis ◽  
Risk Groups ◽  
Low Risk ◽  
Gene Set Enrichment Analysis ◽  
Risk Scores ◽  
Gene Set Enrichment ◽  
Immunotherapy Target

Abstract Background：We aimed to investigate an immune-related long non-coding RNA (lncRNA) signature that may be exploited as a potential immunotherapy target in colon cancer. Materials and methods: Colon cancer samples from The Cancer Genome Atlas (TCGA) containing available clinical information and complete genomic mRNA expression data were used in our study. We then constructed immune-related lncRNA co-expression networks to identify the most promising immune-related lncRNAs. According to the risk score developed from screened immune-related lncRNAs, the high-risk and low-risk groups were separated on the basis of the median risk score, which served as the cutoff value. An overall survival analysis was then performed to confirm that the risk score developed from screened immune-related lncRNAs could predict colon cancer prognosis. The prediction reliability was further evaluated in the independent prognostic analysis and receiver operating characteristic curve (ROC). A principal component analysis (PCA) and gene set enrichment analysis (GSEA) were performed for functional annotation. Results: Information for a total of 514 patients was included in our study. After multiplex analysis, 12 immune-related lncRNAs were confirmed as a signature to evaluate the risk scores for each patient with cancer. Patients in the low-risk group exhibited a longer overall survival (OS) than those in the high-risk group. Additionally, the risk scores were an independent factor, and the Area Under Curve (AUC) of ROC for accuracy prediction was 0.726. Moreover, the low-risk and high-risk groups displayed different immune statuses based on principal components and gene set enrichment analysis.Conclusions: Our study suggested that the signature consisting of 12 immune-related lncRNAs can provide an accessible approach to measuring the prognosis of colon cancer and may serve as a valuable antitumor immunotherapy.

scholarly journals Prognostic Implications of Immune-Related Gene Pairs Signatures in Bladder Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Hui Xiong ◽  
Hui Gao ◽  
Jinding Hu ◽  
Yun Dai ◽  
Hanbo Wang ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
High Risk ◽  
Risk Score ◽  
Immune Cells ◽  
Low Risk ◽  
Gene Set Enrichment Analysis ◽  
Risk Scores ◽  
Related Gene ◽  
Gene Pairs ◽  
Immune Related Gene

Compelling evidence indicates that immune function is correlated with the prognosis of bladder cancer (BC). Here, we aimed to develop a clinically translatable immune-related gene pairs (IRGPs) prognostic signature to estimate the overall survival (OS) of bladder cancer. From the 251 prognostic-related IRGPs, 37 prognostic-related IRGPs were identified using LASSO regression. We identified IRGPs with the potential to be prognostic markers. The established risk scores divided BC patients into high and low risk score groups, and the survival analysis showed that risk score was related to OS in the TCGA-training set ( p < 0.001 ; HR = 7.5 [5.3, 10]). ROC curve analysis showed that the AUC for the 1-year, 3-year, and 5-year follow-up was 0.820, 0.883, and 0.879, respectively. The model was verified in the TCGA-testing set and external dataset GSE13507. Multivariate analysis showed that risk score was an independent prognostic predictor in patients with BC. In addition, significant differences were found in gene mutations, copy number variations, and gene expression levels in patients with BC between the high and low risk score groups. Gene set enrichment analysis showed that, in the high-risk score group, multiple immune-related pathways were inhibited, and multiple mesenchymal phenotype-related pathways were activated. Immune infiltration analysis revealed that immune cells associated with poor prognosis of BC were upregulated in the high-risk score group, whereas immune cells associated with a better prognosis of BC were downregulated in the high-risk score group. Other immunoregulatory genes were also differentially expressed between high and low risk score groups. A 37 IRGPs-based risk score signature is presented in this study. This signature can efficiently classify BC patients into high and low risk score groups. This signature can be exploited to select high-risk BC patients for more targeted treatment.

THU0018 GENETIC FACTORS AND RESPONSE TO RITUXIMAB THERAPY IN SLE

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 222-223
Author(s):  
L. Liu ◽  
A. Amar ◽  
J. Robinson ◽  
I. N. Bruce ◽  
D. Morris ◽  
...  
Keyword(s):  
Risk Score ◽  
Genetic Risk ◽  
Risk Scores ◽  
Research Centre ◽  
Fc Gamma Receptor ◽  
Genetic Risk Scores ◽  
Gamma Receptor ◽  
Genome Wide ◽  
Receptor Locus ◽  
Damage Accrual

Background:The biologic drug Rituximab (anti-CD20) is used therapeutically in SLE, however the clinical response to the therapy, which is expensive, is quite variable. Factors influencing the efficacy have been challenging to determine. The MRC funded MASTERPLANS consortium has investigated prognostic factors that determine the therapeutic response to biologic therapy in SLE. Genetics has not been studied on a large scale in this context. SLE is a complex clinical phenotype, it is likewise a complex genetic trait, although it has recently been shown that polygenic risk scores do have a relationship to the severity of the disease (1). In addition, genetic risk factors for SLE, coded at the IgG Fc gamma receptor locus, have the potential to influence antibody-dependent cell-mediated cytotoxicity.Objectives:To determine whether the genetics influences the clinical outcome of therapy with Rituximab. The study used both genome-wide data in the form of genetic risk scores as well as specific genetic data at a candidate locus, namely the IgG Fc gamma receptor locusMethods:Samples from the BILAG Biologics Register (BILAG BR) of individuals treated with Rituximab were subject to genome-wide genotyping with Illumina GSA V2 chip. Genetic risk scores (GRS) were calculated through a weighted risk sum. Genetic variation at the IgG Fc gamma receptor locus is not captured well on genotyping chips and hence common coding and copy number variation was studied using Multiplex Ligation-dependent Probe Amplification (MLPA) and sequencing.Results:BILAG-BR samples for SLE part of receiving Rituximab therapy were genotyped on GSA chip, 573 samples passed QC and were used in principal components analysis (PCA), among them, 310 samples both have RTX treatment information and GRS calculated. Examining the population using PCA in the informative samples revealed that the largest distinction, European versus African ancestry did not correlate with Rituximab response. When GRS was determined in the Responders versus the Non-responders there was a weak correlation with those with a higher risk score showing a tendency to be in the responder group (Fig. 1). We also examined variation at the IgG Fc gamma receptor locus, polymorphisms of which are associated with SLE and have been correlated with therapeutic outcome in lymphoma (2). In a subset of the BILAG-BR cohort, we show that carriage of the SLE risk allele atFCGR3A(158F) was enriched in the ‘responder at some point’ group compared to the non-responder group (P=0.03, Chi-square).Conclusion:We present preliminary data indicating that genetics at both the genome wide level and at theFCGRlocus show some influence on the outcome of therapy with Rituximab in SLE; more data are required in order to draw firm conclusions.References:[1]Reid S et al. High genetic risk score is associated with early disease onset, damage accrual and decreased survival in systemic lupus erythematosus.Ann Rheum Dis.2019 Dec 11. [Epub ahead of print][2]Weng WK, Levy R. Two immunoglobulin G fragment C receptor polymorphisms independently predict response to rituximab in patients with follicular lymphoma. J Clin Oncol. 2003;21(21):3940–3947.Acknowledgments:King’s and GSTT Biomedical Research Centre and M01665X/1MRC Stratified Medicine grantDisclosure of Interests:Lu Liu: None declared, Ariella Amar: None declared, James Robinson: None declared, Ian N. Bruce Grant/research support from: Genzyme Sanofi, GSK, and UCB, Consultant of: Eli Lilly, AstraZeneca, UCB, Iltoo, and Merck Serono, Speakers bureau: UCB, David Morris: None declared, Tim Vyse: None declared

scholarly journals Primary care risk stratification in COPD using routinely collected data: a secondary data analysis

2019 ◽  
Vol 29 (1) ◽  
Author(s):  
Matthew Johnson ◽  
Lucy Rigge ◽  
David Culliford ◽  
Lynn Josephs ◽  
Mike Thomas ◽  
...  
Keyword(s):  
Primary Care ◽  
Risk Stratification ◽  
Data Quality ◽  
Risk Score ◽  
Secondary Care ◽  
Risk Scores ◽  
Average Risk ◽  
Primary Care Data ◽  
Copd Patients ◽  
Dose Index

AbstractMost clinical contacts with chronic obstructive pulmonary disease (COPD) patients take place in primary care, presenting opportunity for proactive clinical management. Electronic health records could be used to risk stratify diagnosed patients in this setting, but may be limited by poor data quality or completeness. We developed a risk stratification database algorithm using the DOSE index (Dyspnoea, Obstruction, Smoking and Exacerbation) with routinely collected primary care data, aiming to calculate up to three repeated risk scores per patient over five years, each separated by at least one year. Among 10,393 patients with diagnosed COPD, sufficient primary care data were present to calculate at least one risk score for 77.4%, and the maximum of three risk scores for 50.6%. Linked secondary care data revealed primary care under-recording of hospital exacerbations, which translated to a slight, non-significant cohort average risk score reduction, and an understated risk group allocation for less than 1% of patients. Algorithmic calculation of the DOSE index is possible using primary care data, and appears robust to the absence of linked secondary care data, if unavailable. The DOSE index appears a simple and practical means of incorporating risk stratification into the routine primary care of COPD patients, but further research is needed to evaluate its clinical utility in this setting. Although secondary analysis of routinely collected primary care data could benefit clinicians, patients and the health system, standardised data collection and improved data quality and completeness are also needed.

BCL-2 system analysis identifies high-risk colorectal cancer patients

Gut ◽  
2016 ◽  
Vol 66 (12) ◽  
pp. 2141-2148 ◽  
Author(s):  
Andreas U Lindner ◽  
Manuela Salvucci ◽  
Clare Morgan ◽  
Naser Monsefi ◽  
Alexa J Resler ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
High Risk ◽  
System Analysis ◽  
Molecular Subtypes ◽  
Low Risk ◽  
Stage Iii ◽  
Risk Scores ◽  
Apoptosis Pathway ◽  
Risk Of Death ◽  
Increased Risk

ObjectiveThe mitochondrial apoptosis pathway is controlled by an interaction of multiple BCL-2 family proteins, and plays a key role in tumour progression and therapy responses. We assessed the prognostic potential of an experimentally validated, mathematical model of BCL-2 protein interactions (DR_MOMP) in patients with stage III colorectal cancer (CRC).DesignAbsolute protein levels of BCL-2 family proteins were determined in primary CRC tumours collected from n=128 resected and chemotherapy-treated patients with stage III CRC. We applied DR_MOMP to categorise patients as high or low risk based on model outputs, and compared model outputs with known prognostic factors (T-stage, N-stage, lymphovascular invasion). DR_MOMP signatures were validated on protein of n=156 patients with CRC from the Cancer Genome Atlas (TCGA) project.ResultsHigh-risk stage III patients identified by DR_MOMP had an approximately fivefold increased risk of death compared with patients identified as low risk (HR 5.2, 95% CI 1.4 to 17.9, p=0.02). The DR_MOMP signature ranked highest among all molecular and pathological features analysed. The prognostic signature was validated in the TCGA colon adenocarcinoma (COAD) cohort (HR 4.2, 95% CI 1.1 to 15.6, p=0.04). DR_MOMP also further stratified patients identified by supervised gene expression risk scores into low-risk and high-risk categories. BCL-2-dependent signalling critically contributed to treatment responses in consensus molecular subtypes 1 and 3, linking for the first time specific molecular subtypes to apoptosis signalling.ConclusionsDR_MOMP delivers a system-based biomarker with significant potential as a prognostic tool for stage III CRC that significantly improves established histopathological risk factors.

The BARCODE1 pilot study targeting men with increased genetic risk of developing prostate cancer: Examining the feasibility of a community-based screening program using polygenic risk score to target screening.

2021 ◽  
Vol 39 (6_suppl) ◽  
pp. 227-227
Author(s):  
Jana Kathlyn McHugh ◽  
Sarah Benafif ◽  
Holly ni Raghallaigh ◽  
Elizabeth Bancroft ◽  
Zsofia Kote-Jarai ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Primary Care ◽  
Dna Extraction ◽  
Risk Score ◽  
Genetic Risk ◽  
Population Screening ◽  
Low Risk ◽  
Polygenic Risk Score ◽  
Genetic Profiling ◽  
Polygenic Risk

227 Background: A significant proportion of Prostate cancer (PrCa) risk is attributable to heritable risk factors of which only a minority are high risk Mendelian traits. A greater proportion of PrCa is due to the combined effect of multiple low risk variants. There have been approximately 170 single nucleotide polymorphisms (SNPs) identified that are associated with PrCa risk in Europeans. Although each of these confer a low to moderate risk of PrCa, the cumulative risk (polygenic risk score, PRS) of increasing numbers of these risk alleles may confer a substantial relative risk. In PrCa genetic profiling, using PRS, could be used to target population screening to those at highest risk. BARCODE1 is the first study to prospectively review the use of a genetic profile in PrCa screening in the general population in the UK. Methods: Our study invited healthy males aged 55-69 to participate through their Primary Care physicians. Collection kits were mailed to retrieve saliva samples. Genotyping was carried out after DNA extraction using a study specific assay and the PRS was calculated for each participant using the sum of weighted alleles for 130 risk loci. Prostate MRI and Biopsy were then offered to men in the top 10% of the genetic risk profile. Results: 1434 men were invited by letter to participate. The uptake was 26%, of whom 87% of men were eligible for inclusion. Following DNA extraction, genotyping, and quality control checks, data were available for 297 men. 25 participants had PRS in the top 10% and were invited for screening; 19 underwent a prostate MRI, and 18 went on to have a systematic (+/- targeted prostate biopsy. There were 7 diagnoses of PrCa (38.9%). The cancers detected were low-risk and are being managed with Active Surveillance (AS). Results of the first year of follow up will be presented and an update of the main study which aims to recruit 5000 men. Conclusions: The BARCODE1 pilot has shown the feasibility of this population-based study, with an overall uptake of 26% and a cancer incidence of nearly 40%. We have identified approximately 70 Primary care providers who have contributed to the transition to the full BARCODE1 study, which will aim to recruit 5,000 men. The BARCODE1 study results will be important in defining the role of PRS genetic profiling in targeted PrCa population screening. Clinical trial information: IRAS257684.

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